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Missouri University of Science and Technology, Rolla, MO 65409INTEROPERABILITY AMONG HETEROGENEOUS MOBILE MULTI-DATABASES

ABSTRACT

Advances in technology allowmobilenodes to own Databasesand perform Transaction processing in a Mobile Ad-hocNetwork (MANET). The implicit heterogeneity and autonomyof individual database permits us to view the underlyingdatabase system as a multi-database system. Our problemformulation is based on both mobile user and mobile DataServers.In this context we propose interoperability amongheterogeneous, mobile, multi-databases and achieve it with anintegration of underlying network architecture and summaryschema structure. Over semantically inter-related and possiblyreplicated databases; we consider transaction management byusing semantic serializability concept over summary schemamodel. Further, we analyze the effect of mobility on summaryschema structure and on transaction management.

1.

INTRODUCTION

With advances in technology the mobile devicesare capable ofhigher storage to act as databases

to this model. In this environment thenodes or mobile hosts act as database servers.

Taking intoaccounthighly mobile database servers,we consider(manned/un-manned) vehicular network as our suitableapplication domain for this paper. Though, the application canbe set of communicating and collaborating drones inperforming certain tasks; to ground search, rescue and criticalmission; with the later one having lesser mobility of individualnodes.

The implicit heterogeneity and autonomy of the underlyingdistributeddatabase servers permit us to view it as amobilemulti-database system, where each mobilehost can accessmultiple databases to process global transactions.

to mangetransactions over static multi-database. Corresponding to eachsubmitted transaction a global agent is created to take care ofthe actions. Agents here act as an abstraction over

theunderlying network and mapping among schema hierarchy.

Xing et al., [2,3] proposed an optimistic concurrencycontrol algorithm called sequential order dynamic adjustment(SODA) over centralized and distributed mobile ad hocnetwork databases. In SODA a history of committedtransactions is maintained to validate committing transactions.Further, the list is dynamically adjusted during validationprocess toavoid unnecessary aborts. This gives a sequentialordering among the transactions.

In [3] the authors consideredenergy efficient dynamic cluster construction algorithm overMANET, which is also the basis behind many(mobile)

wirelesssensor network due to their energy constraints. In MANETenergy may not always be a constraint and is dependent onspecific application, for example inapplications like vehicularnetwork and co-operating drones accomplishing some specifictask there is no energy constraint; where as, ground search,rescue, and critical mission may have energy constraint.Further, in energy constrained mobile database node it is notalways practical to execute time-consuming transactions,irrespective of dynamic selection of cluster head based oncriteria of energy consumption rate or remaining energy.

Brayner et al., [4]proposed semanticserializability basedconcurrency

control over MANET databases. This has theintrinsic assumption that databases are disjoint and updates on adatabase only depend on values of data in the same database.Though,

in many practical applications databases can be inter-dependentbased on corresponding organizational structure, andthe assumptions of semantic

serializability does not hold. Inthis

approach, global transactions are serialized at each siteusing strict 2PL, while each site must maintain the consistencyof its own local database at the same time. Since, the globalserializability is relaxed and there is no co-ordination amongservers,

and the locks held by the sub-transactionsof the globaltransaction are released once they are completed at the localsites,the limited bandwidth is saved and transaction executiontime is reduced.

overdatabases, parsing the transaction over the schemahierarchy is one way of achieving semantic serializability.Here

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the transaction commits only when all its sub-transactions areready to commit

(similar to strict 2PL scheme) and the issue ofindirect conflict is addressed, as global order is alwaysmaintained.Still,the work in [1] has the implicit assumption ofdisjoint databases and that updates in a database only dependon values of data in that database.

Situation involving updateoperation of a

transactionover some attributesin one databasethat is inter-related with other databases over the

sameattribute(s), or, replications is

not discussed.

The research in [1-4] does not consider the effect ofunderlying networkarchitectureon transaction management. In

this context we consider interoperability among heterogeneousmobile multi-databases as

an integration of networkarchitectureanddatabase concepts for better transactionmanagement. For our study, we take (manned/unmanned)vehicular network as the standard application domain. Insection 2 we consider the

Vehicles or mobilenodes are considered to have data servers (possiblyheterogeneous), and can both initiate and process transactions.Vehicles move along pre-existing roads, have no energyconstraint, relatively lesser computing power than base stations,and have both 802.11 and 3G interfaces.Thus, V2V network isa specific class of MANET.

In contrast,

base stationsconsideredto be fixed, have servers associated with them, havelarger storage, and computing power,andcan communicatewith each other over optical fiber

or wireless.

We consider theserver associated with each base station to have an auxiliarydatabase.

We refer to the area under each base station as zone.If each mobile node uses

V2I communication, then

limited-3Gbandwidth will give rise to congestion, as base stations serveover a much widertransmissionrange.

Thus, we consider thecombination of these two types of communication model calledhybrid model.

Over this hybrid modelclusters are formed involvingvehicles, and base stations to give a hierarchical structure thatfits into the network constraints. Here, we visualize three kindsof clusters:

one involving subset of vehicles

where,communication takes place over WLAN; another involving

each

basestation and

the set of cluster heads within its zone;the third

static clusterinvolving only bases stations.

Since,there is no energy constraint the best possible way to form theclusters is to use relative mobility and signal strength asparameters, as the network mobility changes frequently. Thecorresponding cluster head is selected based on somepredefined heuristics (like ratio of total number of mobile nodeswithin the communication range to the number of mobile nodeswith above average signal level, relative displacement).

Inliterature there exists a number of clustering and cluster head

election algorithms for VANET [5,6].

Further, in the MANETdomain the dynamic clustering and cluster head algorithmsneed to consider energy constraint in the algorithms [7].Fig. 1represents this basic hierarchical network structure.

In the following section we consider the neededdatabasearchitecture overthe discussed network hierarchy to facilitateInteroperability over mobile multi-databases.

3. INTEROPERABILITY AMONG HETEROGENEOUSMOBILE MULTI-DATABASES

In order to considerinteroperability among heterogeneousmobile multi-databases,

We assume the database designer/ linguist has alreadydefined the semantic and structural relationship amongattributes for a specific application domain (here vehicularnetwork). On this an automatic, dynamic schemasummarization algorithm is used to generate the summaryschema hierarchy or to map the incoming transaction tosemantically

and structurally

similar schema.

Further, we consider the summeryschema model beingbuilt up at four

levels.

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(a)

WLAN-Summary Schema:Each

vehicle

or mobilenode

has a database and its

corresponding

localschema.

When a local cluster (WLAN) isformedand acluster headis elected, all the local schemaswithin it are used to

generate the correspondingWLAN-summary schema at the cluster head. Thissummary schema is built automatically anddynamically (as mobile nodes can change) usingschema summarization algorithm. The lowestlevelcells of the schema table points to the IPaddress of the respective vehicles with matchedsemantic and structural attribute, and the cells ofupper level schema table points to thecorresponding matched lower level schema table.

(b)

WWAN-Summary Schema/

Intra-Zonal SummarySchema:

Each cluster head ina zone communicatewith the corresponding base station.The WLAN-summary schemas are used to build the intra-zonalsummary schema at the base station,

usingtheautomatic

schema summarization algorithm. Theintra-zonal summary schema is build over all themobile nodes of the respective zone.As in theWLAN–summary schema, the cells

of the lowestlevel

schema table here points to the IP address ofthe respective mobile node and of the upper levelschema tables points to the lower level schematable based onsemantic and structural matching.

(c)

Auxiliary Summary Schema: This is either acomplete or partial replica of the intra-summaryschema model. This is built (replicated) when amobile node leaves a zone, and its correspondingdata is copied to the auxiliarydatabase. Theauxiliary database and the corresponding schemais used to parse the transaction when there is nomatched schema is found in theintra-zonalsummary schema and the transaction refers to thatzone only. One such situation is, suppose a zone is

completely empty and a transaction is directed tothat zone to gather information about roadcondition; in this case the auxiliary summaryschema is used to scan the auxiliary database forany possible information. The auxiliary DB in anycase contains the most updated informationcorresponding to any set of attributes, when thereis no vehicle with the matchedschemaattributes.This is because, leaving vehicles update theauxiliary database if there is no other node withmatching schema attributes and there is readorupdate operation

being performed on it.In case ofupdate operation the updated value is kept on theauxiliary database for future use. We will considerthe details of the use of auxiliary schema andauxiliary database in Section 3

(d)

Inter-Zonal Summary Schema: This summaryschema isstatic

one and can be built directly bythe database designer, owing to the fixed basestations. This is built over geographic roadnetwork and corresponding base station’s subnetIP address, which we mentioned earlier. This isused to find either destination base stations for ageographic region or gateway base stations to thedestination.

This acts as a DNS server in network.

The minute details of the above summary schema structurefalls under the domainofschema summarization

without worrying about its current zone. If thedestination for transaction processing is outside the currentzone,

then the specific route to the destination is taken;

withoutbroadcastingthrough all adjacent base stations.

We will see the use of these above schema structures in

providing interoperability during transaction execution.

3.2.Interoperability with Multiple Summary SchemaStructure

The

multiple layers of summary schema structureallowtransactions to be processed under their most precise domain.Suitable domain for processing transactions can be determinedinn the following way using summary schema:

Once a transaction is issued at a node:

(1) The semantic and structural matching is done to checkwhether it involves own database or not. If it involves only owndatabase domain and

(a) A read operation,

then the information is accessedlocally.

(b) An

update operation,

then the correspondingattributes are updated

and the WLAN summary schema issearched for any other matching node and the attributevalue is updated at the respective nodes.

(2) If the outcome of the semantic and structural matchingon own database is NULL, then WLAN-summary schema issearched for any matching node. If thematch is found then:

(a) If it is a read operation, then the information isextracted from one of the matching nodes.

(b) If it is an update operation then all matched nodesare updated.

(3) If the outcome of matching with respect to WLAN-summary schema is NULL, then it is passed to the bases stationvia the cluster head.There it is matched with respect totheinter-zonal summary schema to find its corresponding zone andthe base station.

(I) If it is the same base station, then the transaction ismatched against the intra-zonal summary schema node to findthe destination node to process the transaction.

(II) If it is a different base station,then the transaction isrouted to the destination subnet IP address and matched againstthe intra-zonal summary schema node at the destination basestation.

Corresponding to read or update operation the suitablestepsare taken as in (2).(a) and (2).(b).

We see that,

the above summary schema based approachallows us to route the transaction to the destination in a guidedmanner,

rather than making an undirected broadcast. In this

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discussion we limited our discussion to focus oninteroperability, but there is more to the transaction execution.

In the above we considered the transactions to be simpleones, involving single nodes. In reality single transactionprocessing can span multiple nodes and nodes themselves maynot be semantically and structurally disjoint. We consider thedetails of thisin transaction management in the followingsection.

4.TRANSACTION MANAGEMENT OVER SUMMARY

SCHEMA MODEL

In order to achieve higher performance transactions areinterleaved. The concept underneath concurrent transactionexecution, while maintaining the atomicity and consistencyproperty is to have a sequential execution of the conflictingtransactions. By conflicting transactions we mean the

set oftransactions that want to access the same data (semantically andstructurally) at the same time and one of them is an updateoperation. One approach to achieve sequential order amongconflicting transactionsisthrough semantic and structuralparsing. Since, schema represents a

semantic and structuralabstraction of the underlying attributes, it is justified to parsethrough the summary schema hierarchy of [10].Further,summary schema hierarchy provides parallelism by allowingmultiple entry points

for a transaction. An incoming transactioncan be matched with summary schema nodes at all levels of thesummary schema hierarchy for possible matching.In [1] theauthorsconsidered summary schema hierarchy, but implicitlyassumed disjoint and non-replicated database. Further, theyhave used agents as an abstractionover the underlying networkandfor parsing over the schema hierarchy.

Hereweconsider databases that can have semantically andstructurally identical attributes,andcanbecompletelyreplicated. In addition, transaction

execution can spanoversemantically and structurally related databases involvingcommon attributes. Further, we consider non-agent basedmodel, where transactions are passed over the network aspackets and parsed over the summary schema hierarchy by asemantic parser.

After getting parsed over the summary schemamodel, transactions reach the desired destination database

Inthis section we consider two aspects of mobility: if mobilitywill have any effect on performance of the summary schemastructure and how transactions will behandled in

case ofmobile nodes that process and/or submit

transactions.

Summaryschema structure

is a logical hierarchical graph based onsemantic and structural heterogeneity. The map along this graphis a traversal from generalized to precise attribute that satisfythe semantics and structural property of all higher-level nodes.In our example vehicularnetwork application, all mobile nodesare highly mobile. In the following paragraph we consider thedifferent scenarios, where summary schema is built andmaintained and analyze effect of mobility on each.

Let’s first consider the WLAN. Here, the cluster headcontains the summary schema hierarchy for the nodes within itsown communication range. The cells of the lowest level SSNpoints to the IP address of the vehicles. When a vehicle movesaway from the cluster and hence,

out of the communicationrange of the cluster head, the respective cell pointer at thelowest level SSN is set to NULL. At the same time,

there mightbe other mobile nodes within the range of the cluster headwithmatchingsemantics, so the lowest level SSN may not getdeleted. If there is no node with the matching semanticattributes of the SSN,

then the pointer to this nodeisset toNULL at its upper levelSSN. Thus, the deletionoperationis anoutcome of the heterogeneity of semantics and structuralinformation of the mobile node and the number ofheterogeneous nodes moving out. In the worst case ifthecluster is dissolved that is,

all the nodes move out of the cluster(irrespective of whether heterogeneous or homogeneous) thenthe graph becomes empty. An upper level SSN node is

set toNULL,

iff all its lower level nodes (children) are empty. If weobserve, then each of the summary schema node is like a tablethat is populated (a pointer is added) when a match is foundwith its metadata fields and is eliminated when there is nomatch. This hierarchical graph structure is stored in memory,like a routing table in router that is populated and deleted as thenodes are connected and removed in its network. If we considerthe cost of eliminating SSN nodes in the logical structure, then

in the worst case it is O

(h); where h isthe height of thesemantic tree.Further, in most application domains, mobilenodes move in groups, with relative distance among nodes

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remaining same in most part. Thus, it is less likely that therewill be changes to the cell pointerin WLAN.

Similarly, when anode is added to the cluster and a (new) cluster head is elected,the summary schema is built. The cost (time) to build this graphdepends on the efficiency of the semantic translator. Theworst-case

time to add a pointer to the already existing SSN node(table) or,

to add a new SSN isO (h), where h is the height ofthe schema graph. In

case of a new SSN node creation,

thenodes in the upper layer need to

be adjusted to accommodatethe addition.

This

toohas worst case cost O

(h), giving theoverall worst case cost to be O (h). In case of WWAN, when anode moves outof its

current zone the respective cell pointerinthe corresponding intra-zonal schemais set to NULL.Similarly, when a node enters a zone thecorresponding intra-zonal summary schema is populated. The procedure and cost issame,

as in case of WLAN-summaryschema structure.

For inter-zonal summary schema there is no effect ofmobility. Further, the effect of mobility on auxiliary summary

schema structure is discussed in the following paragraph, alongwith transactions.

First, weconsiderthat a transaction is allocated tothematched node,

if

it has not initiated any handoff procedure.

Now,

if the node

initiates handoff while executing thetransaction,

then the following situations can happen.

(1)

The transaction is completed before the handoffprocedure is

done. In this case the result isreturned to the destination via base station and/orcluster heads.

(2)

Transaction is yet to be completed andthe handoff procedure is initiated.

(a)

The transaction is aborted over that database.If there isadditionalmatchingnodes in thesame zonethen the transaction is restartedexecuting there.

Further, all other allocatedtransactions to the transiting nodeare

transferredto the suitable matched node.

(b)

There is no matched node from the intra-zonal summary schema. The state of thedatabasethat is the values of thecorresponding database is stored in theauxiliary database. Theassociatedsummaryschema model

the transaction does not have any matchingnode over theintra-zonal schema, then theauxiliary summary schema is searched forpossible matching. If a match is found, thetransaction is transferredto auxiliary database andis

executed

there.

When a node processing a transaction, moves out of aWLANframework,

and

is within the zone; it sendsthe resultback to the cluster head via the new cluster headand basestation. Any cluster head keeps track of the submitted butwaiting transactions till it gets the corresponding result anddelivers it to the requested node.

Thus, an

auxiliary database is updated when a node leavesa zone and there is no other node with the matchedsemantic/structural information.

Now, we consider thesituation where the requesting nodehas moved out of its WLAN or WWAN network. In either casethe result is routed to the node via base station and cluster

head.

The result is returned to the base station of the transaction-processing node. From here, theresult is forwarded to thecurrent location of the node.

the lack of energy constraintand resource constraint makes it suitable for multi-databasetransaction processing, where we considered summary schemamodel. Further, we considered transaction management over

inter-related and replicated databases.

Finally, we consideredthe effect of mobility over summary schema hierarchy andtransaction management. Related to this paper we need to givethe correctness proof of the transaction management approachover mobile multi-database. For future research in this domain,we would like to consider novel concurrency control algorithmsthat will be suitable for resource and energy constrained mobilead hoc networks. This algorithm should be independent of thedynamic cluster head selection